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Further optimize bfmatcher by passing macros.

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peng xiao 2013-04-12 16:51:36 +08:00
parent 113b7584e0
commit 6eefd276cf
2 changed files with 60 additions and 93 deletions
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47
modules/ocl/src/brute_force_matcher.cpp
View File

@ -16,6 +16,7 @@
//
// @Authors
// Nathan, liujun@multicorewareinc.com
// Peng Xiao, pengxiao@outlook.com
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
@ -61,6 +62,8 @@ namespace cv
}
}
static const int OPT_SIZE = 100;
template < int BLOCK_SIZE, int MAX_DESC_LEN/*, typename Mask*/ >
void matchUnrolledCached(const oclMat &query, const oclMat &train, const oclMat &/*mask*/,
const oclMat &trainIdx, const oclMat &distance, int distType)
@ -74,9 +77,9 @@ void matchUnrolledCached(const oclMat &query, const oclMat &train, const oclMat
int m_size = MAX_DESC_LEN;
vector< pair<size_t, const void *> > args;
static const int OPT_SIZE = 40;
char opt [OPT_SIZE] = "";
sprintf(opt, "-D block_size=%d -D max_desc_len=%d", block_size, m_size);
sprintf(opt, "-D distType=%d -D block_size=%d -D max_desc_len=%d", distType, block_size, m_size);
if(globalSize[0] != 0)
{
args.push_back( make_pair( sizeof(cl_mem), (void *)&query.data ));
@ -90,7 +93,6 @@ void matchUnrolledCached(const oclMat &query, const oclMat &train, const oclMat
args.push_back( make_pair( sizeof(cl_int), (void *)&train.rows ));
args.push_back( make_pair( sizeof(cl_int), (void *)&train.cols ));
args.push_back( make_pair( sizeof(cl_int), (void *)&query.step ));
args.push_back( make_pair( sizeof(cl_int), (void *)&distType ));
std::string kernelName = "BruteForceMatch_UnrollMatch";
@ -116,9 +118,9 @@ void match(const oclMat &query, const oclMat &train, const oclMat &/*mask*/,
int block_size = BLOCK_SIZE;
vector< pair<size_t, const void *> > args;
static const int OPT_SIZE = 40;
char opt [OPT_SIZE] = "";
sprintf(opt, "-D block_size=%d", block_size);
sprintf(opt, "-D distType=%d -D block_size=%d", distType, block_size);
if(globalSize[0] != 0)
{
args.push_back( make_pair( sizeof(cl_mem), (void *)&query.data ));
@ -132,7 +134,6 @@ void match(const oclMat &query, const oclMat &train, const oclMat &/*mask*/,
args.push_back( make_pair( sizeof(cl_int), (void *)&train.rows ));
args.push_back( make_pair( sizeof(cl_int), (void *)&train.cols ));
args.push_back( make_pair( sizeof(cl_int), (void *)&query.step ));
args.push_back( make_pair( sizeof(cl_int), (void *)&distType ));
std::string kernelName = "BruteForceMatch_Match";
@ -160,9 +161,9 @@ void matchUnrolledCached(const oclMat &query, const oclMat &train, float maxDist
int m_size = MAX_DESC_LEN;
vector< pair<size_t, const void *> > args;
static const int OPT_SIZE = 40;
char opt [OPT_SIZE] = "";
sprintf(opt, "-D block_size=%d -D max_desc_len=%d", block_size, m_size);
sprintf(opt, "-D distType=%d -D block_size=%d -D max_desc_len=%d", distType, block_size, m_size);
if(globalSize[0] != 0)
{
args.push_back( make_pair( sizeof(cl_mem), (void *)&query.data ));
@ -180,7 +181,6 @@ void matchUnrolledCached(const oclMat &query, const oclMat &train, float maxDist
args.push_back( make_pair( sizeof(cl_int), (void *)&trainIdx.cols ));
args.push_back( make_pair( sizeof(cl_int), (void *)&query.step ));
args.push_back( make_pair( sizeof(cl_int), (void *)&trainIdx.step ));
args.push_back( make_pair( sizeof(cl_int), (void *)&distType ));
std::string kernelName = "BruteForceMatch_RadiusUnrollMatch";
@ -201,9 +201,9 @@ void radius_match(const oclMat &query, const oclMat &train, float maxDistance, c
int block_size = BLOCK_SIZE;
vector< pair<size_t, const void *> > args;
static const int OPT_SIZE = 40;
char opt [OPT_SIZE] = "";
sprintf(opt, "-D block_size=%d", block_size);
sprintf(opt, "-D distType=%d -D block_size=%d", distType, block_size);
if(globalSize[0] != 0)
{
args.push_back( make_pair( sizeof(cl_mem), (void *)&query.data ));
@ -221,7 +221,6 @@ void radius_match(const oclMat &query, const oclMat &train, float maxDistance, c
args.push_back( make_pair( sizeof(cl_int), (void *)&trainIdx.cols ));
args.push_back( make_pair( sizeof(cl_int), (void *)&query.step ));
args.push_back( make_pair( sizeof(cl_int), (void *)&trainIdx.step ));
args.push_back( make_pair( sizeof(cl_int), (void *)&distType ));
std::string kernelName = "BruteForceMatch_RadiusMatch";
@ -300,9 +299,9 @@ void knn_matchUnrolledCached(const oclMat &query, const oclMat &train, const ocl
int m_size = MAX_DESC_LEN;
vector< pair<size_t, const void *> > args;
static const int OPT_SIZE = 40;
char opt [OPT_SIZE] = "";
sprintf(opt, "-D block_size=%d -D max_desc_len=%d", block_size, m_size);
sprintf(opt, "-D distType=%d -D block_size=%d -D max_desc_len=%d", distType, block_size, m_size);
if(globalSize[0] != 0)
{
args.push_back( make_pair( sizeof(cl_mem), (void *)&query.data ));
@ -316,7 +315,6 @@ void knn_matchUnrolledCached(const oclMat &query, const oclMat &train, const ocl
args.push_back( make_pair( sizeof(cl_int), (void *)&train.rows ));
args.push_back( make_pair( sizeof(cl_int), (void *)&train.cols ));
args.push_back( make_pair( sizeof(cl_int), (void *)&query.step ));
args.push_back( make_pair( sizeof(cl_int), (void *)&distType ));
std::string kernelName = "BruteForceMatch_knnUnrollMatch";
@ -335,9 +333,9 @@ void knn_match(const oclMat &query, const oclMat &train, const oclMat &/*mask*/,
int block_size = BLOCK_SIZE;
vector< pair<size_t, const void *> > args;
static const int OPT_SIZE = 40;
char opt [OPT_SIZE] = "";
sprintf(opt, "-D block_size=%d", block_size);
sprintf(opt, "-D distType=%d -D block_size=%d", distType, block_size);
if(globalSize[0] != 0)
{
args.push_back( make_pair( sizeof(cl_mem), (void *)&query.data ));
@ -351,7 +349,6 @@ void knn_match(const oclMat &query, const oclMat &train, const oclMat &/*mask*/,
args.push_back( make_pair( sizeof(cl_int), (void *)&train.rows ));
args.push_back( make_pair( sizeof(cl_int), (void *)&train.cols ));
args.push_back( make_pair( sizeof(cl_int), (void *)&query.step ));
args.push_back( make_pair( sizeof(cl_int), (void *)&distType ));
std::string kernelName = "BruteForceMatch_knnMatch";
@ -370,6 +367,8 @@ void calcDistanceUnrolled(const oclMat &query, const oclMat &train, const oclMat
int m_size = MAX_DESC_LEN;
vector< pair<size_t, const void *> > args;
char opt [OPT_SIZE] = "";
sprintf(opt, "-D distType=%d", distType);
if(globalSize[0] != 0)
{
args.push_back( make_pair( sizeof(cl_mem), (void *)&query.data ));
@ -384,11 +383,10 @@ void calcDistanceUnrolled(const oclMat &query, const oclMat &train, const oclMat
args.push_back( make_pair( sizeof(cl_int), (void *)&train.rows ));
args.push_back( make_pair( sizeof(cl_int), (void *)&train.cols ));
args.push_back( make_pair( sizeof(cl_int), (void *)&query.step ));
args.push_back( make_pair( sizeof(cl_int), (void *)&distType ));
std::string kernelName = "BruteForceMatch_calcDistanceUnrolled";
openCLExecuteKernel(ctx, &brute_force_match, kernelName, globalSize, localSize, args, -1, query.depth());
openCLExecuteKernel(ctx, &brute_force_match, kernelName, globalSize, localSize, args, -1, query.depth(), opt);
}
}
@ -402,6 +400,8 @@ void calcDistance(const oclMat &query, const oclMat &train, const oclMat &/*mask
int block_size = BLOCK_SIZE;
vector< pair<size_t, const void *> > args;
char opt [OPT_SIZE] = "";
sprintf(opt, "-D distType=%d", distType);
if(globalSize[0] != 0)
{
args.push_back( make_pair( sizeof(cl_mem), (void *)&query.data ));
@ -415,11 +415,10 @@ void calcDistance(const oclMat &query, const oclMat &train, const oclMat &/*mask
args.push_back( make_pair( sizeof(cl_int), (void *)&train.rows ));
args.push_back( make_pair( sizeof(cl_int), (void *)&train.cols ));
args.push_back( make_pair( sizeof(cl_int), (void *)&query.step ));
args.push_back( make_pair( sizeof(cl_int), (void *)&distType ));
std::string kernelName = "BruteForceMatch_calcDistance";
openCLExecuteKernel(ctx, &brute_force_match, kernelName, globalSize, localSize, args, -1, query.depth());
openCLExecuteKernel(ctx, &brute_force_match, kernelName, globalSize, localSize, args, -1, query.depth(), opt);
}
}
@ -676,12 +675,14 @@ void cv::ocl::BruteForceMatcher_OCL_base::matchCollection(const oclMat &query, c
}
CV_Assert(query.channels() == 1 && query.depth() < CV_64F);
const int nQuery = query.rows;
ensureSizeIsEnough(1, nQuery, CV_32S, trainIdx);
ensureSizeIsEnough(1, nQuery, CV_32S, imgIdx);
ensureSizeIsEnough(1, nQuery, CV_32F, distance);
matchDispatcher(query, (const oclMat *)trainCollection.ptr(), trainCollection.cols, masks, trainIdx, imgIdx, distance, distType);
exit:
return;
@ -771,6 +772,7 @@ void cv::ocl::BruteForceMatcher_OCL_base::knnMatchSingle(const oclMat &query, co
const int nQuery = query.rows;
const int nTrain = train.rows;
if (k == 2)
{
ensureSizeIsEnough(1, nQuery, CV_32SC2, trainIdx);
@ -1045,6 +1047,7 @@ void cv::ocl::BruteForceMatcher_OCL_base::radiusMatchSingle(const oclMat &query,
const int nQuery = query.rows;
const int nTrain = train.rows;
CV_Assert(query.channels() == 1 && query.depth() < CV_64F);
CV_Assert(train.type() == query.type() && train.cols == query.cols);
CV_Assert(trainIdx.empty() || (trainIdx.rows == query.rows && trainIdx.size() == distance.size()));

106
modules/ocl/src/opencl/brute_force_match.cl
View File

@ -66,37 +66,30 @@ int bit1Count(float x)
return (float)c;
}
#ifndef distType
#define distType 0
#endif
#if (distType == 0)
#define DIST(x, y) fabs((x) - (y))
#elif (distType == 1)
#define DIST(x, y) (((x) - (y)) * ((x) - (y)))
#elif (distType == 2)
#define DIST(x, y) bit1Count((uint)(x) ^ (uint)(y))
#endif
float reduce_block(__local float *s_query,
__local float *s_train,
int lidx,
int lidy,
int distType
int lidy
)
{
/* there are threee types in the reducer. the first is L1Dist, which to sum the abs(v1, v2), the second is L2Dist, which to
sum the (v1 - v2) * (v1 - v2), the third is humming, which to popc(v1 ^ v2), popc is to count the bits are set to 1*/
float result = 0;
switch(distType)
#pragma unroll
for (int j = 0 ; j < block_size ; j++)
{
case 0:
for (int j = 0 ; j < block_size ; j++)
{
result += fabs(s_query[lidy * block_size + j] - s_train[j * block_size + lidx]);
}
break;
case 1:
for (int j = 0 ; j < block_size ; j++)
{
float qr = s_query[lidy * block_size + j] - s_train[j * block_size + lidx];
result += qr * qr;
}
break;
case 2:
for (int j = 0 ; j < block_size ; j++)
{
result += bit1Count((uint)s_query[lidy * block_size + j] ^ (uint)s_train[(uint)j * block_size + lidx]);
}
break;
result += DIST(s_query[lidy * block_size + j], s_train[j * block_size + lidx]);
}
return result;
}
@ -105,35 +98,14 @@ float reduce_multi_block(__local float *s_query,
__local float *s_train,
int block_index,
int lidx,
int lidy,
int distType
int lidy
)
{
/* there are threee types in the reducer. the first is L1Dist, which to sum the abs(v1, v2), the second is L2Dist, which to
sum the (v1 - v2) * (v1 - v2), the third is humming, which to popc(v1 ^ v2), popc is to count the bits are set to 1*/
float result = 0;
switch(distType)
#pragma unroll
for (int j = 0 ; j < block_size ; j++)
{
case 0:
for (int j = 0 ; j < block_size ; j++)
{
result += fabs(s_query[lidy * max_desc_len + block_index * block_size + j] - s_train[j * block_size + lidx]);
}
break;
case 1:
for (int j = 0 ; j < block_size ; j++)
{
float qr = s_query[lidy * max_desc_len + block_index * block_size + j] - s_train[j * block_size + lidx];
result += qr * qr;
}
break;
case 2:
for (int j = 0 ; j < block_size ; j++)
{
//result += popcount((uint)s_query[lidy * max_desc_len + block_index * block_size + j] ^ (uint)s_train[j * block_size + lidx]);
result += bit1Count((uint)s_query[lidy * max_desc_len + block_index * block_size + j] ^ (uint)s_train[j * block_size + lidx]);
}
break;
result += DIST(s_query[lidy * max_desc_len + block_index * block_size + j], s_train[j * block_size + lidx]);
}
return result;
}
@ -152,8 +124,7 @@ __kernel void BruteForceMatch_UnrollMatch_D5(
int query_cols,
int train_rows,
int train_cols,
int step,
int distType
int step
)
{
@ -191,7 +162,7 @@ __kernel void BruteForceMatch_UnrollMatch_D5(
//synchronize to make sure each elem for reduceIteration in share memory is written already.
barrier(CLK_LOCAL_MEM_FENCE);
result += reduce_multi_block(s_query, s_train, i, lidx, lidy, distType);
result += reduce_multi_block(s_query, s_train, i, lidx, lidy);
barrier(CLK_LOCAL_MEM_FENCE);
}
@ -247,8 +218,7 @@ __kernel void BruteForceMatch_Match_D5(
int query_cols,
int train_rows,
int train_cols,
int step,
int distType
int step
)
{
const int lidx = get_local_id(0);
@ -283,7 +253,7 @@ __kernel void BruteForceMatch_Match_D5(
barrier(CLK_LOCAL_MEM_FENCE);
result += reduce_block(s_query, s_train, lidx, lidy, distType);
result += reduce_block(s_query, s_train, lidx, lidy);
barrier(CLK_LOCAL_MEM_FENCE);
}
@ -344,8 +314,7 @@ __kernel void BruteForceMatch_RadiusUnrollMatch_D5(
int train_cols,
int bestTrainIdx_cols,
int step,
int ostep,
int distType
int ostep
)
{
const int lidx = get_local_id(0);
@ -371,7 +340,7 @@ __kernel void BruteForceMatch_RadiusUnrollMatch_D5(
//synchronize to make sure each elem for reduceIteration in share memory is written already.
barrier(CLK_LOCAL_MEM_FENCE);
result += reduce_block(s_query, s_train, lidx, lidy, distType);
result += reduce_block(s_query, s_train, lidx, lidy);
barrier(CLK_LOCAL_MEM_FENCE);
}
@ -405,8 +374,7 @@ __kernel void BruteForceMatch_RadiusMatch_D5(
int train_cols,
int bestTrainIdx_cols,
int step,
int ostep,
int distType
int ostep
)
{
const int lidx = get_local_id(0);
@ -432,7 +400,7 @@ __kernel void BruteForceMatch_RadiusMatch_D5(
//synchronize to make sure each elem for reduceIteration in share memory is written already.
barrier(CLK_LOCAL_MEM_FENCE);
result += reduce_block(s_query, s_train, lidx, lidy, distType);
result += reduce_block(s_query, s_train, lidx, lidy);
barrier(CLK_LOCAL_MEM_FENCE);
}
@ -462,8 +430,7 @@ __kernel void BruteForceMatch_knnUnrollMatch_D5(
int query_cols,
int train_rows,
int train_cols,
int step,
int distType
int step
)
{
const int lidx = get_local_id(0);
@ -501,7 +468,7 @@ __kernel void BruteForceMatch_knnUnrollMatch_D5(
//synchronize to make sure each elem for reduceIteration in share memory is written already.
barrier(CLK_LOCAL_MEM_FENCE);
result += reduce_multi_block(s_query, s_train, i, lidx, lidy, distType);
result += reduce_multi_block(s_query, s_train, i, lidx, lidy);
barrier(CLK_LOCAL_MEM_FENCE);
}
@ -609,8 +576,7 @@ __kernel void BruteForceMatch_knnMatch_D5(
int query_cols,
int train_rows,
int train_cols,
int step,
int distType
int step
)
{
const int lidx = get_local_id(0);
@ -645,7 +611,7 @@ __kernel void BruteForceMatch_knnMatch_D5(
barrier(CLK_LOCAL_MEM_FENCE);
result += reduce_block(s_query, s_train, lidx, lidy, distType);
result += reduce_block(s_query, s_train, lidx, lidy);
barrier(CLK_LOCAL_MEM_FENCE);
}
@ -752,8 +718,7 @@ kernel void BruteForceMatch_calcDistanceUnrolled_D5(
int query_cols,
int train_rows,
int train_cols,
int step,
int distType)
int step)
{
/* Todo */
}
@ -768,8 +733,7 @@ kernel void BruteForceMatch_calcDistance_D5(
int query_cols,
int train_rows,
int train_cols,
int step,
int distType)
int step)
{
/* Todo */
}